53 citations · 230 across the 34 of their papers we have counts for
15 papers · 1 filter
Conversational Analysis of Daily Dialog Data using Polite Emotional Dialogue Acts
Chandrakant Bothe, Stefan Wermter
Many socio-linguistic cues are used in conversational analysis, such as emotion, sentiment, and dialogue acts. One of the fundamental cues is politeness, which linguistically posse…
DRILL: Dynamic Representations for Imbalanced Lifelong Learning
Kyra Ahrens, Fares Abawi, Stefan Wermter
Continual or lifelong learning has been a long-standing challenge in machine learning to date, especially in natural language processing (NLP). Although state-of-the-art language m…
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)
A. Sutherland, S. Bensch, T. Hellström +2
Sentiment analysis has transitioned from classifying the sentiment of an entire sentence to providing the contextual information of what targets exist in a sentence, what sentiment…
Leveraging Recursive Processing for Neural-Symbolic Affect-Target Associations
A. Sutherland, S. Magg, S. Wermter
Explaining the outcome of deep learning decisions based on affect is challenging but necessary if we expect social companion robots to interact with users on an emotional level. In…
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
Chandrakant Bothe, Cornelius Weber, Sven Magg +1
The recognition of emotion and dialogue acts enriches conversational analysis and help to build natural dialogue systems. Emotion interpretation makes us understand feelings and di…
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples
Marcus Soll, Tobias Hinz, Sven Magg +1
Adversarial examples are artificially modified input samples which lead to misclassifications, while not being detectable by humans. These adversarial examples are a challenge for…